TL;DR: The “MCP vs A2A” framing is a category error. They sit on different axes of an agent system: MCP is the vertical protocol connecting one agent down to its tools and data, while A2A is the horizontal protocol connecting agents across each other A2A vs MCP: Key Differences for Agent System Architects — Vercel. An implementation-grounded study from the University of York (arXiv 2607.23884, July 2026) built the same four-agent coordination loop twice — once on MCP, once on A2A — and found MCP delivers a lighter coordination model (1,255 vs 1,898 lines of code, 4 vs 10 coordination primitives, 2 vs 6 coordination stages per interaction) while A2A’s long-lived Task abstraction buys native multi-turn, stateful coordination at the cost of substantially more machinery A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. The emerging production answer is not either/or: MCP inside each agent, A2A between agents A2A vs MCP: Key Differences for Agent System Architects — Vercel.

The one-axis model: capabilities below, collaborators beside

Every operational difference between the two protocols traces back to a single assumption about the other side of the connection. MCP assumes the other end is a capability the agent controls — a database, an API, a deterministic service. A2A assumes the other end is a peer that reasons independently, refuses requests, and asks clarifying questions A2A vs MCP: Key Differences for Agent System Architects — Vercel. MCP describes capabilities; A2A describes collaborators A2A vs MCP: Key Differences for Agent System Architects — Vercel.

MCP’s architecture is strictly client–server: a host (the LLM application) instantiates one client per server, and servers expose three first-class primitives — resources (data), tools (executable functions), and prompts (templates) — negotiated over JSON-RPC 2.0 Model Context Protocol Specification (2025-06-18) — modelcontextpro…. A2A is peer-oriented: a client agent submits work to a remote agent that hosts its own reasoning, state, and opaque internals A Comparative Study of MCP and A2A for Inter-Agent Coordination in…A2A Protocol documentation — a2a-protocol.org.

Flowchart of an orchestrator agent, peer agents B and C, and three tools, connected by A2A agent-to-agent calls and MCP tool calls.
Figure: how an orchestrator agent uses A2A to delegate to peer agents and MCP to call tools.

The A2A protocol itself is explicit about the division: “MCP is for agent-to-tool communication… A2A is for agent-to-agent communication” — and “not a replacement for MCP” A2A Protocol documentation — a2a-protocol.org. The protocol docs’ own canonical build recipe is: build with any framework, equip with MCP (or any tool layer), communicate with A2A A2A Protocol documentation — a2a-protocol.org.

Wire-level transports: one RPC dialect, different binding strategies

Both protocols speak JSON-RPC 2.0 at the application layer, but they bind to the wire differently.

MCP defines two standard transports — stdio for local subprocesses and Streamable HTTP for remote servers A2A vs MCP: Key Differences for Agent System Architects — Vercel. Since the 2026-07-28 revision, Streamable HTTP is deliberately stateless: a single POST-only endpoint, no protocol-level sessions, no Mcp-Session-Id header, no initialize handshake A2A vs MCP: Key Differences for Agent System Architects — Vercel. Every request is self-describing — version and capabilities ride in _meta, and routing metadata is mirrored into MCP-Protocol-Version, Mcp-Method, and Mcp-Name headers so intermediaries can inspect traffic without parsing bodies A2A vs MCP: Key Differences for Agent System Architects — Vercel. A conforming tools/call is a plain, cacheable-looking POST Model Context Protocol Specification (2025-06-18) — modelcontextpro…A2A vs MCP: Key Differences for Agent System Architects — Vercel:

POST /mcp HTTP/1.1
Host: mcp.example.com
Content-Type: application/json
Accept: application/json, text/event-stream
MCP-Protocol-Version: 2026-07-28
Mcp-Method: tools/call
Mcp-Name: get_weather

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_weather",
    "arguments": { "city": "London" }
  }
}

A2A takes the opposite approach to binding: the application protocol is defined transport-agnostically (protobuf is the source of truth), with three normative bindings — JSON-RPC 2.0 over HTTP, gRPC over HTTP/2, and HTTP+JSON/REST — and updates delivered by polling, SSE, or webhooks A2A vs MCP: Key Differences for Agent System Architects — Vercela2aproject/A2A — GitHub. A task submission over the JSON-RPC binding looks like A Comparative Study of MCP and A2A for Inter-Agent Coordination in…a2aproject/A2A — GitHub:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tasks/send",
  "params": {
    "id": "task-7f3a",
    "contextId": "thread-42",
    "message": {
      "role": "user",
      "parts": [
        { "kind": "text", "text": "Generate a domain model for a library system" }
      ]
    }
  }
}

The binding multiplicity is a real operational cost. Polling, SSE, and webhooks are all valid per spec, so you must verify which update-delivery mechanism a given remote agent actually implements before building against it A2A vs MCP: Key Differences for Agent System Architects — Vercel. MCP’s single-POST statelessness, by contrast, means load balancers, CDNs, and gateways can treat agent traffic like ordinary HTTP — the very property that motivated the rewrite A2A vs MCP: Key Differences for Agent System Architects — Vercel.

State: the Task is the atom of A2A; statelessness is the point of MCP

This is the deepest divergence. A2A’s core abstraction is the Task — a stateful, long-running unit of work tracked by both sides from submission to a terminal state, grouped into logical threads by contextId, and producing Artifacts that can stream incrementally as work progresses A2A vs MCP: Key Differences for Agent System Architects — Vercel. Messages, by contrast, are the lightweight path for trivial interactions that need no tracking A2A vs MCP: Key Differences for Agent System Architects — Vercel. The task lifecycle is protocol-level, not application-level A Comparative Study of MCP and A2A for Inter-Agent Coordination in…:

State diagram of an A2A task moving from submitted through working, with input-required and auth-required pauses, to one of four terminal states: completed, canceled, failed, or rejected.
Figure: the A2A task lifecycle. Tasks move from submitted to working and end in completed, canceled, failed or rejected.

The paused states are the tell. input-required exists specifically so a remote agent can halt mid-task, ask for clarification, and resume without losing task identity — a negotiation pattern a stateless function call cannot represent A Comparative Study of MCP and A2A for Inter-Agent Coordination in…A2A vs MCP: Key Differences for Agent System Architects — Vercel. The A2A-based implementation in the York study leans on exactly this: a constant task ID and context ID persist across retry cycles, letting artifacts and status events reconstruct the entire interaction history A Comparative Study of MCP and A2A for Inter-Agent Coordination in….

MCP’s 2026-07-28 rewrite is deliberately the opposite: stateless by design, with any server instance able to serve any request A2A vs MCP: Key Differences for Agent System Architects — Vercel. Task semantics did briefly appear in MCP core (November 2025 revision: tasks/get, tasks/cancel, status notifications) but were moved out of core into an official extension in the July 2026 revision — a signal to pin your spec revision if you build on them A2A vs MCP: Key Differences for Agent System Architects — Vercel. The York paper found the practical consequence: in the MCP-based system, conversational state and task lifecycle must be “implemented explicitly at the application layer,” whereas A2A provides them natively A Comparative Study of MCP and A2A for Inter-Agent Coordination in….

Discovery: tools/list versus the well-known card

Discovery encodes the trust boundary each protocol assumes A2A vs MCP: Key Differences for Agent System Architects — Vercel:

{
  "name": "Semantic Reviewer",
  "description": "Validates generated models against a requirements description",
  "url": "https://agents.example.com/semantic-reviewer",
  "version": "1.2.0",
  "skills": [
    { "id": "validate-model", "name": "Validate domain model" }
  ],
  "capabilities": { "streaming": true, "pushNotifications": false },
  "security": { "authenticationSchemes": ["bearer"] }
}

Note the asymmetry: A2A’s card solves discovery, not selection. It is registry-light — finding the right remote agent still depends on knowing where to look, and credentials are exchanged out of band, declared but not delivered by the protocol A2A vs MCP: Key Differences for Agent System Architects — Vercel.

What the empirical study actually measured

arXiv 2607.23884 (submitted 26 July 2026, University of York) is the first implementation-grounded comparison of MCP and A2A used for inter-agent coordination rather than tool access A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. The setup: a fixed four-agent collaboration — a collaboration agent orchestrating a solution agent plus syntactic and semantic supervisor agents — solving a software engineering task (generate an Emfatic/EMF domain model from a natural-language prompt), with both implementations sharing the same coordination algorithm and the same LLM (qwen2.5-coder:32b), differing only in protocol A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. Validation ran on 30 prompts, 10 straightforward and 20 of higher complexity A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. Real output from the solution agent, validated end-to-end A Comparative Study of MCP and A2A for Inter-Agent Coordination in…:

class Library {
  attr String name;
  val Book[*] books;
  val Author[*] authors;
}
class Book {
  attr String title;
  attr int pageCount;
  ref Author author;
}

The complexity delta is stark — measured with cloc, excluding config A Comparative Study of MCP and A2A for Inter-Agent Coordination in…:

Metric MCP A2A Delta
Lines of code 1,255 1,898 +51%
Coordination primitives 4 10 +150%
Coordination stages per interaction 2 6 +200%

A2A’s six stages (agent discovery, task creation, message dispatch, task state progression, artifact propagation, completion handling) versus MCP’s two (transport initialisation, tool invocation) reflect “the richer protocol-level workflow semantics and lifecycle management capabilities provided by A2A” — and correspondingly a larger coordination failure surface A Comparative Study of MCP and A2A for Inter-Agent Coordination in….

Against the seven requirements derived from prior literature and industry partners (banking, aerospace, immersive tech, IoT), the scores were A Comparative Study of MCP and A2A for Inter-Agent Coordination in…:

Requirement MCP A2A
R1: Agent discoverability ✓ ✓
R2: Multi-part messaging ✓ ✓
R3: Multi-turn conversations ✗ ✓
R4: Asynchronous and streaming ✓ ✓
R5: Agent observability ~ ~
R6: Interoperability ✓ ✓
R7: Access control ✓ ✓

Two findings deserve emphasis. First, R3 is the only differentiator: A2A natively supports multi-turn clarification via input-required; MCP requires servers to implement their own context tracking A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. Second, neither protocol solves observability natively — no protocol-level tracing, no super-task IDs to correlate a tree of tasks and sub-tasks; both implementations had to bolt on Langfuse/Phoenix-style OpenTelemetry instrumentation at the application layer A Comparative Study of MCP and A2A for Inter-Agent Coordination in…. MCP’s 2026-07-28 revision does now document traceparent/tracestate propagation in _meta, which narrows but does not close that gap A2A vs MCP: Key Differences for Agent System Architects — Vercel. The authors are careful to frame the results as “design observations from an empirical experience report rather than general claims of protocol suitability” — the coordination pattern evaluated is deliberately narrow A Comparative Study of MCP and A2A for Inter-Agent Coordination in….

The production pattern: both protocols, one architecture

Every row of the comparison traces back to the same design decision, and so does the architecture that is emerging in production: MCP manages each agent’s access to tools and data; A2A coordinates between agents A2A vs MCP: Key Differences for Agent System Architects — Vercel. The A2A project itself ships this as the reference mental model — “MCP is for agent-to-tool communication… A2A is for agent-to-agent communication” — and the majority of application-oriented work combining both protocols follows exactly this layered structure A Comparative Study of MCP and A2A for Inter-Agent Coordination in… A2A Protocol documentation — a2a-protocol.org.

Two organizations: a client agent in Organization A and a remote agent in Organization B, each calling its own MCP servers, connected by a bidirectional A2A link.
Figure: each organization's agent reaches its own tools over MCP, and the two agents talk to each other over A2A.

That architecture obliges you to operate: durable HTTPS endpoints (A2A’s long-lived endpoint per remote agent, not short-lived functions), published Agent Cards, out-of-band credential infrastructure, task lifecycle state, one MCP server per tool or data source, and correlated logging across every A2A message and MCP call A2A vs MCP: Key Differences for Agent System Architects — Vercel. Treat those as first-class infrastructure, not afterthoughts A2A vs MCP: Key Differences for Agent System Architects — Vercel.

Decision rules that fall out of the protocol analysis and the empirical results:

  1. Everything in one codebase, one team — skip both protocols. Framework-native subagents or plain function calls add less serialization and no interoperability tax A2A vs MCP: Key Differences for Agent System Architects — Vercel.
  2. The remote side is deterministic (same input → same output) — expose it as an MCP tool. Keep reasoning in the calling agent A2A vs MCP: Key Differences for Agent System Architects — Vercel.
  3. The remote side reasons autonomously, runs long, needs back-and-forth, or crosses an organizational boundary — that is a peer, not a tool; use A2A A2A vs MCP: Key Differences for Agent System Architects — Vercel.
  4. You need cross-boundary delegation and tool access — run both: A2A between agents, MCP inside each A2A vs MCP: Key Differences for Agent System Architects — Vercel.
  5. Coordination is constrained and in-process — the York results show MCP can carry it with ~51% fewer lines of code and a far smaller coordination surface, at the price of hand-rolled conversation state and lifecycle handling A Comparative Study of MCP and A2A for Inter-Agent Coordination in….
  6. Multi-turn negotiation is the core interaction — reach for A2A’s Task lifecycle; MCP will make you rebuild input-required at the application layer A Comparative Study of MCP and A2A for Inter-Agent Coordination in….

Governance: two foundations, one trajectory

Both protocols now live under neutral open governance. Anthropic donated MCP to the Linux Foundation on 9 December 2025 as a founding project of the new Agentic AI Foundation (AAIF), alongside Block’s goose and OpenAI’s AGENTS.md, with platinum members including AWS, Anthropic, Bloomberg, Cloudflare, Google, Microsoft, and OpenAI — MCP alone counted more than 10,000 published servers at the time Linux Foundation Announces the Formation of the Agentic AI Foundati…. A2A, originally developed by Google and donated to the Linux Foundation, is Apache-2.0 licensed, maintained by a technical steering committee with seats at AWS, Cisco, Google, IBM Research, Microsoft, Salesforce, SAP, and ServiceNow, and reached 1.0 stable in March 2026 with public support from 150+ organizations A2A Protocol documentation — a2a-protocol.orgA2A vs MCP: Key Differences for Agent System Architects — Vercela2aproject/A2A — GitHub. IBM Research’s ACP (Agent Communication Protocol) merged into A2A under LF AI & Data in August 2025, consolidating the agent-to-agent layer further A2A vs MCP: Key Differences for Agent System Architects — Vercel. Maturity-wise: A2A 1.0 adds multi-tenancy and a web-aligned architecture built for the load balancers and gateways teams already run A2A vs MCP: Key Differences for Agent System Architects — Vercel; MCP’s surface is stable but its task semantics are settling inside an official extension, its registry is in preview, and it still has no memory primitive — plan around those gaps A2A vs MCP: Key Differences for Agent System Architects — Vercel.

Bottom line

MCP and A2A are not competing standards; they are two orthogonal layers of the same stack, and the empirical record now backs that up A Comparative Study of MCP and A2A for Inter-Agent Coordination in…A2A Protocol documentation — a2a-protocol.orgA2A vs MCP: Key Differences for Agent System Architects — Vercel. MCP wins where the other side is a deterministic capability and the priority is a small coordination surface; A2A wins where the other side is an autonomous peer and the priority is stateful, multi-turn negotiation A Comparative Study of MCP and A2A for Inter-Agent Coordination in…A2A vs MCP: Key Differences for Agent System Architects — Vercel. The protocol-level question to ask before reaching for either is the one Vercel’s guide leads with: what does your architecture assume about the other side of the connection? A2A vs MCP: Key Differences for Agent System Architects — Vercel

Sources:

References

A Comparative Study of MCP and A2A for Inter-Agent Coordination in… A Comparative Study of MCP and A2A for Inter-Agent Coordination in LLM-Based Systems — arXiv:2607.23884 A2A Protocol documentation — a2a-protocol.org A2A Protocol documentation — a2a-protocol.org Model Context Protocol Specification (2025-06-18) — modelcontextpro… Model Context Protocol Specification (2025-06-18) — modelcontextprotocol.io A2A vs MCP: Key Differences for Agent System Architects — Vercel A2A vs MCP: Key Differences for Agent System Architects — Vercel Linux Foundation Announces the Formation of the Agentic AI Foundati… Linux Foundation Announces the Formation of the Agentic AI Foundation — linuxfoundation.org a2aproject/A2A — GitHub a2aproject/A2A — GitHub

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